How Vidu 2.0 Enhances AI Video Content Consistency

AI video tools like Keling and Hailuo are widely used. I must say, Keling 1.6 performs exceptionally well, and Vidu has quickly followed suit by releasing version 2.0.

The core features include:

Version 2.0 boasts significant performance leaps. The generation speed of seconds not only represents a data improvement but also a revolution in workflow. I remember using version 1.5, where each generation was as slow as a snail. The incredible speed makes the creative process seamless. This enhancement is a lifesaver for commercial projects that require repeated adjustments.

Multi-Subject Consistency

The evolution of multi-subject collaboration: Vidu’s multi-subject collaboration technology is a benchmark in the industry. During testing, I was pleasantly surprised to find that version 2.0 has elevated this technology to new heights:

Character interaction scenes: Interactions between characters are more natural, with eye contact and body language being very convincing.
Prop interaction effects: The physical attributes of objects are represented more accurately, with realistic rendering of weight and texture.
Spatial relationship handling: The layout of multiple elements in the scene is more logical, giving the image a stronger sense of space.

Based on extensive testing, I found that appropriately enlarging the subject area of reference images significantly increases success rates. This small tip has been a great help in practical applications.

Expression Transfer

This community-driven innovation is eye-catching. Through precise expression selection and transfer, Vidu 2.0 can not only restore basic expressions but also capture subtle emotional changes. From my observations, this feature is particularly useful in the following scenarios:

Brand endorsement video production
Educational content development
Social media marketing materials

It’s worth mentioning that when dealing with continuous expression changes, it’s advisable to prepare a set of progressive expression references to achieve smoother transitions.

Some have even tested the effects with animations:

Camera Control

The same material can achieve various camera effects, greatly enhancing the reuse value of the material.By using camera prompts, you can control the movement of the camera and combine two types of shots.

My professional advice is to choose high-resolution images when preparing materials, so that the quality can be maintained even during local enlargements. Also, ensure consistent lighting in the reference images for better results.

Start and End Frames

Start and end frames have always been a widely used feature in AI video applications. In October 2024, Vidu first launched the start and end frame feature, and this version 2.0 has shown significant improvements in performance!

Version 2.0 will intelligently analyze scene elements and add just the right transition effects. For instance, when switching from an urban scene to a natural scene, it will gradually introduce plant elements for a smooth transition.

Stylization Stability

This is also crucial; maintaining a consistent style in generated videos is vital. Avoiding sudden changes in artistic style and visual breakdowns is one of the most important aspects of AI video.

Here, we can control the style of the image, and subsequently control the style of the generated video.

Finally, let’s take a look at the price comparison with various AI video platforms:

For the same 720p video, Vidu costs less than 30 cents per second. So in the future, for image-to-video and text-to-video generation, besides Keling and Hailuo, you can try Vidu. The results are indeed impressive.

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